Brewer Spotlight

Is Jhoulys Chacin Milwaukee’s Ace of the Future?


BREW MATHs conducts a highly detailed review of Jhoulys Chacin’s career up to this point. We use everything from PITCHf/x data to heat maps in order to break down what you can expect from Milwaukee’s ‘Number One’ in 2019…


Before we jump into the numbers let’s first consider the man behind the stats. Chacin is 30 years old, has played nine years and is entering the last year of his contract with The Crew ($6.75M). Being in a contract year serves to amplify the fact that his career is at a fork in the road.

Chacin was signed by Colorado as an International FA in 2004 and immediately became a lauded prospect. In 2009, he jumped straight from AA-Ball to The MLB and got his feet wet on The Big Stage. In 2010, his full first year, he led all rookies in strikeouts and seemed to be a superstar in the making. 2011 came with heightened expectations and for the first half of the season he exceeded them all. However, the second half of the season went poorly and fans suddenly did not know what to think. The next few years would be filled with the same ups & downs, most of the low points stemming from injury. Then when things could not seem to get worse, Chacin was released by the the team that developed him on 03/22/2015.

For the next couple of years, he found himself bouncing around the minor leagues and pitching in spot roles with Cleveland, Arizona, Atlanta, and LAA. Then in 2016, he found a good fit with San Diego and went 13-10 with a WHIP of 1.27. David Stearns took note of his potential and on 12/01/2017, The Brewers signed Chacin to a two-year $15.5M deal. At the time, this seemed to be a risk for a small market club. However, any doubt was quickly erased as Chacin anchored a rotation that came one game from The World Series.

So the million dollar question: Which Jhoulys Chacin will we see moving forward? The guy who bounced all over the league for almost a decade or The Ace that Milwaukee rode to The NL Central Title? BREW MATHs digs in…


Before we start, let me warn you, the first graph might make you nauseous. This was done intentionally to show you how our most advanced pitching metrics all end narrowing between 4.00 and 4.50 for Chacin:


When you see statistical variation narrow definitively over time (as above) it suggests we are ‘dialing in’ upon the pitcher’s true identity. What we see above looks troubling at first since an xFIP of ~4.50 is poor at best.

That said, Miller Park is friendly to hitters, more often than not:


Click on Miller to see BREW MATHsummary of Park Factor

That is exactly why the statistics with minus symbols (-) are included in the graph above… they are park adjusted versions of the stat. Let’s only consider those for a moment: ERA- & FIP- trend down, while xFIP- sharply trends up.

Let’s briefly define what each metric is to understand why they differ:

FIP: Fielding-Independent Pitching; attempts to eliminate the effects of fielding when rating a pitcher’s performance.

FIP-: Adjusted for park and league

xFIP: Uses ‘expected home runs’ (Fly Ball % x league average HR rate on FBs) instead of raw HR totals, like FIP does.

xFIP-: Uses ‘expected home runs’ instead of HRs & is park adjusted

So the difference between ERA-, FIP- & xFIP- is a byproduct of the difference between ‘fly ball rates’ and ‘HR rates.’ Chacin gave up a lot of fly balls last year but kept 9.3% of them in the park last year (league HR/FB Average is typically ~9.5%). While his career mark is 10.1%.

It suddenly becomes paramount to know what opponent’s quality of contact since he is allowing a lot of balls into play and more importantly, into the air…


The graph tells us that batters make a lot of contact against Chacin. Do not get too attached to these as they are based on human observation and very prone to error. It does not change the fact that he is being hit…

This then raises the question: Did he just get lucky in keeping more fly balls in the park OR is it a reflection of him honing certain skills? For us to understand something like that we need to know how hard he is throwing, how his pitches are moving and any changes to his repertoire.

For that, we must consult PITCHf/x data. It uses two fancy cameras to track velocity & movement from the pitcher’s hand until it reaches home plate. A lot of data is generated in the time it takes for a fastball to reach the catcher. In fact, it is how ‘exit velocity’ became common nomenclature in baseball circles. Thankfully MLB began logging this data in 2009 when Chacin broke into the league. We have the benefit of analyzing all 20,117 pitches he has thrown as a Big Leaguer. That will be considered in the next section, ‘Pitch Placement.’ Before we get to that, let’s consider a couple more concrete data points.

The graph below will show us that Jhoulys is a “fly ball pitcher.” This surprisingly can be more effective than a “ground ball pitcher” with one big caveat… you can’t let too many fly balls turn into homers. The only reliable way to ensure that is to consistently keep hitters off-balance and guessing. Keep this in mind as we expand upon our analysis:


For context, the table (below) shows us that batting average is actually lowest on fly balls in general. They are often playable but that ones that are not tend to do more damage than the average grounder. Hence, the higher ISO & wOBA with fly balls:


Before we bring on the PITCHf/x data, let’s contextualize things with one more pretty graph showing a more common set of metrics. These rate stats show that as Chacin initially learned to control his pitches his strike outs went down in equal proportion. He now enters the second half of his prime is clearly not a “power pitcher” as the following data shows. Both his K & BB rates are considered ‘below average’ by FanGraphs standards:



So how the heck is he still so effective? This IS the same guy who posted these numbers in 2018:

15 – 8 / 3.50 ERA / 1.163 WHIP / 2.2 WAR

Baseball is a game known for it’s long relationship with improbability and luck. Is it possible that Milwaukee’s Beloved Ace just got lucky?



Where Chacin is locating his pitches is a great place to start. It can give us clues if there have been any general shifts in his approach and a gives us a sense of his control. Both of the heat maps below reflect overall pitch percentage; the top is where Chacin has placed pitches over his entire career while the lower one is 2018 alone.



2018 Season Alone:


This is a reassuring on a basic level since it reflects a pitcher who is learning to use the corners more to his advantage. To validate this, Chacin did have the highest Edge% of his career in 2018 at 30.6%.

He also has seen opponents Whiff% rise consistently over the last three years (19.7%, 20.5%, and 21.3% last year). In addition, MLB tracks how many “barreled balls” are hit off of Chacin (i.e. optimal contact). In 2015, 12.2% of hits off of him were barreled. Last year, only 6.3% were…

Suddenly things don’t look as bad anymore. In fact, as we stray further away from ‘power’ metrics and get deeper into ‘control’ metrics, Chacin’s true talent level comes into focus.



The Statcast Pitch Arsenal makes it clear to see that Chacin has 6 pitches at his disposal (!) but he typically has only used three. He relies mainly upon his slider and sinker but mixes a 4FB in, too.

Below, the pitch arsenal data is expanded upon. The dashes (on the L) and gears (on the R) represent league averages:


Again, this confirms what we already know… that Chacin is not a “power pitcher.” So how does he do it? Some stats have alluded that it is his command / control but nothing has been definitive. Let’s look at how each pitch actually performs to see where he makes up his ground:


Chacin’s success starts to come into focus when we understand what this table is telling us:

  •  JC has used five pitches consistently over his career and he banks primarily on his slider, sinker and four seamer. Also of note, he releases all of these at about the same spot and with the same arm angle also maximizing confusion for the poor hitter.
  •  Over his career, JC will typically strike you out with one of three pitches: The slider, the change up or the curve. Odds are it will be a slider – he throws it more than the other two combined.
  •  Hitters make good contact with his fastball but he typically keeps them from leaving the park. If opponents are going to take Chacin deep it will be when he throws his change up or slider.
  • The fastball generates a fair amount of ground balls. Speaking of which…
  •  His sinker is not an effective strikeout pitch but leads to a lot of ground balls. The slider and curve are his most effective strikeout pitches and also induce a lot of pop outs.

The Sabermetric pitching outcomes above are over his career so let’s isolate 2018 for comparative purposes:


Aha! Last year saw Chacin focus more on his core pitches (slider, sinker, 4FB) and limit the amount he threw his less reliable pitches (Split, Change, Curve). This is key and starts to cue us in to exactly how he has success. Consider this:


As you proceed to the right on the chart, notice how ‘the noise’ begins to die down. The red (slider) and grey (sinker) lines eventually overtake the black (4FB) line that initially dominated the scene. The marginal, less used pitches are used less and less. Last year, the change up, curve and splitter were all basically dropped.

So, there it is! Chacin is refining his approach and seems to be learning how (and when) to use the pitches he has mastered while limiting the pitches he is less effective with. The final diagram puts it all together…

(Yellow = Slider / Orange = Sinker / Red = 4FB / Blue = SF / Green = Change):


  • Chacin has learned to throw sinkers early in the count in an attempt to produce more ground balls and limit risk. When he is behind in the count he goes away from the slider a bit more and relies upon the sinker and fast ball. Again, reinforcing how his approach has become increasingly built upon strategic control. Imbalance.
  • As he gets ahead in the count, he throws more sliderswhich he gets the highest Whiff%  rate with… by far (36.60%)! Even when his back is against the wall (i.e. full count) he typically goes for the throat with the slider.
  • The imbalance he creates in the hitter’s mind is based upon a horizontal distribution and vertical ball movement. This largely eliminates the hitter’s legs from the equation. They have to shorten their stride which helps lead to the high pop-out rate and the ‘warning track power’ his pitches induce.


Chacin has learned to refine his control and has evolved into a different pitcher than when he was with Colorado. Chacin’s stats have to be taken with a grain of salt since the vast majority of them came while pitching in hitter’s parks. Despite all the challenges he has faced, he’s mastered three pitches that work very well in concert:

  1. Slider – Strikeout pitch; used in lower risk situations (i.e. when he is ahead in the count). It is his most utilized pitch and has become increasingly more relied upon over his career. His money maker.
  2. Sinker – Has continually improved the usefulness of this pitch over his career with a crescendo in ’18. It complements his slider nicely. The difference between the two pitches is about 11mph and 25 degrees of real estate. It keeps batters on their heels and leads to weaker contact. Chacin has learned to rely on this imbalance to keep the fly balls in the park and batters off the bases. He initially struggled with his approach but seemed to perfect it last year. The sinker is key in his evolution; it makes the slider that much more un-hittable (and vice-versa).
  3. 4 Seamer – Chacin uses this as his stabilizer when he is behind in the count. It is not effective on its own. Hitter’s make above average contact with it and are able to generate an average HR rate when it’s thrown. The fact he uses it more judiciously allows it to be more effective when thrown.

Overall, this year will be a big one for Chacin… He’s in a contract year after years of bouncing around the league and finds himself on a real contender. No matter how many stats we consider, the time is now…


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